About
Updated info: https://www.nichele.eu/
Fields of study
Academic disciplines
Research groups
Research projects
Ongoing research projects
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AI-Mind
The goal of the research is to reduce the burden of dementia by developing novel, AI-based tools.
Completed research projects
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FeLT- Futures of Living Technologies
From a perspective of ecological crisis, FeLT engages in the relations and intersections that occur between human beings, living environments and machines.
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Hybrid Deep Learning Cellular Automata Reservoir (DeepCA)
DeepCA is a long-term time horizon project seeking the integration of biological and artificial intelligence.
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SOCRATES
Seeking radical breakthroughs toward efficient and powerful data analysis available everywhere.
Publications and research
Scientific publications
Valderhaug, Vibeke Devold; Ramstad, Ola Huse; van de Wijdeven, Rosanne Francisca;
Heiney, Kristine
;
Nichele, Stefano
; Sandvig, Axel; Sandvig, Ioanna
(2024).
Micro-and mesoscale aspects of neurodegeneration in engineered human neural networks carrying the LRRK2 G2019S mutation.
Frontiers in Cellular Neuroscience.
Vol. 18.
https://doi.org/10.3389/fncel.2024.1366098
Farner, Jørgen Jensen; Huse Ramstad, Ola;
Nichele, Stefano
;
Heiney, Kristine
(2024).
Local Delay Plasticity Supports Generalized Learning in Spiking Neural Networks.
Villani, Marco; Cagnoni, Stefano; Serra, Roberto (Ed.).
Artificial Life and Evolutionary Computation. WIVACE 2023.. p. 241-255.
Springer.
https://doi.org/https://doi.org/10.1007/978-3-031-
Bhandari, Shailendra
;
Nichele, Stefano
;
Denysov, Sergiy
;
Lind, Pedro
(2024).
How quantum and evolutionary algorithms can help each other: two examples.
arXiv.
https://doi.org/10.48550/arXiv.2408.00448
Glover, Tom Eivind
; Jahren, Ruben; Francesco, Martinuzzi;
Lind, Pedro
;
Nichele, Stefano
(2024).
A sensitivity analysis of cellular automata and heterogeneous topology networks: partially-local cellular automata and homogeneous homogeneous random boolean networks.
International Journal of Parallel, Emergent and Distributed Systems.
https://doi.org/10.1080/17445760.2024.2396334
Lindell, Trym
; Huse Ramstad, Ola; Sandvig, Ioanna; Sandvig, Axel;
Nichele, Stefano
(2024).
Chaotic Time Series Prediction in Biological Neural Network Reservoirs on Microelectrode Arrays.
Hirose, Akira; Ishibuchi, Hisao (Ed.).
2024 International Joint Conference on Neural Networks (IJCNN). p. 1-10.
IEEE conference proceedings.
https://doi.org/10.1109/IJCNN60899.2024.10650567
Pietropolli, Gloria;
Nichele, Stefano
; Medvet, Eric
(2024).
The Role of the Substrate in CA-based Evolutionary Algorithms.
Li, Xiandong; Handl, Julia (Ed.).
GECCO '24: Proceedings of the Genetic and Evolutionary Computation Conference. p. 768-777.
Association for Computing Machinery (ACM).
https://doi.org/https://doi.org/10.1145/3638529.36
Jain, Sanyam;
Nichele, Stefano
(2024).
Frequency-Histogram Coarse Graining in Elementary and 2-Dimensional Cellular Automata.
Nordic Machine Intelligence (NMI).
Vol. 3.
https://doi.org/10.5617/nmi.10458
Jain, Sanyam; Shrestha, Aarati;
Nichele, Stefano
(2024).
Capturing Emerging Complexity in Lenia.
Villani, Marco; Cagnoni, Stefano; Serra, Roberto (Ed.).
Artificial Life and Evolutionary Computation. WIVACE 2023.. p. 41-53.
Springer.
https://doi.org/https://doi.org/10.1007/978-3-031-
Glover, Tom Eivind
;
Lind, Pedro
;
Yazidi, Anis
; Osipov, Evgeny;
Nichele, Stefano
(2023).
Investigating Rules and Parameters of Reservoir Computing with Elementary Cellular Automata, with a Criticism of Rule 90 and the Five-Bit Memory Benchmark.
42 p.
Complex Systems.
Vol. 32.
https://doi.org/10.25088/ComplexSystems.32.3.309
Pierro, Alessandro;
Heiney, Kristine
; Shrivastava, Shamit; Marcucci, Gulia;
Nichele, Stefano
(2023).
Optimization of a Hydrodynamic Computational Reservoir through Evolution.
Silva, Sara; Paquete, Luis (Ed.).
GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference. p. 202-210.
Association for Computing Machinery (ACM).
https://doi.org/10.1145/3583131.3590355
